High-reliability aircraft communication encryption method based on quantum neural network

Abstract

The invention discloses a high-reliability aircraft communication encryption method based on a quantum neural network. The aircraft communication encryption method comprises the following steps: collecting and preprocessing aircraft communication original data; the method comprises the following steps: initializing a quantum neuron state by using a quantum state superposition principle, and determining an initial connection weight value of a quantum neural network by calculating probability amplitude values of different quantum gate operations so as to construct an initial quantum neural network structure; generating an encryption key according to quantum bits of the output layer of the quantum neural network; for aircraft communication data to be transmitted, an encrypted data ciphertext is obtained according to the encryption key, a quantum key distribution technology is utilized to generate and distribute the key, and the ciphertext and the key are transmitted through a communication channel; and the receiving end receives the ciphertext and decrypts and verifies the security in the ciphertext transmission process. According to the method, the aircraft communication data is encrypted based on the quantum neural network, and the security in the aircraft communication process is improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing, and in particular to a high-reliability aircraft communication encryption method based on quantum neural network. Background Art

[0002] With the increase in computing power, especially the development of quantum computers, traditional encryption algorithms are at risk of being cracked. Therefore, a more secure and reliable encryption method is needed to protect sensitive data in aircraft communications. Quantum neural networks can not only generate highly secure keys by combining quantum key distribution with quantum neural networks, but also achieve efficient encryption and decryption processing of data, and can adaptively adjust encryption strategies to cope with potential security threats. Based on this, the present invention proposes a high-reliability aircraft communication encryption method based on quantum neural networks. Summary of the invention

[0003] The present invention provides a high-reliability aircraft communication encryption method based on quantum neural network, comprising:

[0004] S10, collecting and preprocessing aircraft communication raw data;

[0005] S20, using the quantum state superposition principle to initialize the quantum neuron state, and determining the initial connection weight value of the quantum neural network by calculating the probability amplitude value of different quantum gate operations, thereby constructing the initial quantum neural network structure;

[0006] S30, generating an encryption key according to the quantum bits of the output layer of the quantum neural network;

[0007] S40, for the aircraft communication data to be transmitted, obtaining encrypted data ciphertext according to the encryption key, generating and distributing the key using quantum key distribution technology, and transmitting the ciphertext and the key through the communication channel;

[0008] S50: The receiving end receives the ciphertext, decrypts it, and verifies the security of the ciphertext during transmission.

[0009] As described above, a high-reliability aircraft communication encryption method based on quantum neural network is described, wherein the preprocessing of the original aircraft communication data includes using fast Fourier transform to obtain the signal frequency distribution, and using a sliding average filtering algorithm to calculate the signal strength value after noise reduction.

[0010] As described above, a high-reliability aircraft communication encryption method based on a quantum neural network is described, wherein the construction of an initial quantum neural network structure is divided into the following sub-steps: quantum state superposition initialization; calculation of probability amplitude values ​​of different quantum gate operations; determination of initial connection weight values ​​of the quantum neural network; and construction of an initial quantum neural network structure based on the initial connection weight values.

[0011] As described above, a high-reliability aircraft communication encryption method based on a quantum neural network is described, wherein the generation of an encryption key is divided into the following sub-steps: selecting random seed data and encoding it into a format suitable for quantum neural network input; inputting the encoded random seed data into the quantum neural network for result measurement; and converting the result measurement of the quantum neural network output layer into an encryption key value of a fixed length via a hash algorithm.

[0012] As described above, a high-reliability aircraft communication encryption method based on quantum neural network is provided, wherein the encrypted data ciphertext is the result of bitwise XOR of the aircraft communication data and the encryption key.

[0013] As described above, a high-reliability aircraft communication encryption method based on quantum neural network is described, wherein the ciphertext is transmitted to the sender through a communication channel, and the communication channel includes a satellite communication link and a microwave communication link.

[0014] As described above, a high-reliability aircraft communication encryption method based on quantum neural network is described, in which the influence of different communication channels on transmission needs to be considered during the transmission process of the communication channel, and error correction coding and orthogonal amplitude modulation are used to improve the reliability of data transmission.

[0015] The present invention also provides a high-reliability aircraft communication encryption system based on quantum neural network, comprising:

[0016] Acquisition and processing module: used to collect and pre-process the original data of aircraft communication;

[0017] Building module: Use the principle of quantum state superposition to initialize the quantum neuron state, calculate the probability amplitude values ​​of different quantum gate operations, determine the initial connection weight values ​​of the quantum neural network, and thus construct the initial quantum neural network structure;

[0018] Key generation module: Generates encryption keys based on quantum bits in the output layer of the quantum neural network;

[0019] Communication channel module: for aircraft communication data to be transmitted, the encrypted data ciphertext is obtained according to the encryption key, the key is generated and distributed using quantum key distribution technology, and the ciphertext and key are transmitted through the communication channel;

[0020] Receiving and verification module: The receiving end receives the ciphertext and decrypts and verifies the security of the ciphertext during transmission.

[0021] The beneficial effects achieved by the present invention are as follows: The present invention encrypts aircraft communication data based on quantum neural networks, thereby improving the security of aircraft communication processes. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0023] Figure 1 This is a flow chart of a high-reliability aircraft communication encryption method based on quantum neural network provided in Example 1 of the present application.

[0024] Figure 2 This is a schematic diagram of a high-reliability aircraft communication encryption system based on a quantum neural network provided in Example 2 of the present application. DETAILED DESCRIPTION

[0025] The following is a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0026] Embodiment 1

[0027] like Figure 1 As shown, the first embodiment of the present application provides a high-reliability aircraft communication encryption method based on quantum neural network, including:

[0028] S10: Collect and pre-process original aircraft communication data.

[0029] Aircraft communication data comes from a wide range of sources, including sensor data on the aircraft, which is used to collect flight status data, including speed, altitude, attitude, etc., control command data transmitted by the communication module, and multimedia data such as voice and images. These data are collected through a dedicated data acquisition interface at a specific sampling frequency to ensure data integrity and real-time performance.

[0030] The collected aircraft communication data is subjected to fast Fourier transform to obtain the signal frequency distribution. The collected time domain original signal is divided into several data segments, each data segment contains N sampling points. A fast Fourier transform operation is performed on each data segment to convert the time domain signal into a frequency domain signal. The specific formula is Among them, x(n) represents the time domain signal, which is the sampling value on the time series n, representing the signal strength of the original data of the aircraft communication at a certain moment. n represents the time series index, from 0 to N-1, which represents the serial number of the sampling point, used to identify each sampling value in the time domain signal. N represents the number of signal sampling points, that is, the total number of samples taken for the time domain signal. k represents the frequency index, from 0 to N-1, representing each frequency component in the frequency domain signal. Different k values ​​correspond to different frequencies. X(k) represents the frequency domain signal, which is the signal strength at frequency k after fast Fourier transform, reflecting the energy distribution of the original time domain signal at this frequency.

[0031] Combined with the sliding average filtering algorithm, the signal strength value after noise reduction is calculated. For the frequency domain signal after fast Fourier transform, a sliding average window is set with a window length of M. The signal in the window is averaged by moving one sampling point each time to obtain the signal strength value after noise reduction. The specific formula is: Among them, X(n) represents the input signal, y(n) represents the filtered output signal, which is the noise reduction signal strength value obtained after sliding average filtering, and M represents the length of the sliding average window, which determines the number of signal points involved in the average calculation.

[0032] According to the frequency distribution calculated by fast Fourier transform and the signal strength value after sliding average filtering, the noise signal that obviously deviates from the normal range is removed. The denoised signal is normalized and the signal value range is mapped to the [0,1] interval.

[0033] S20. Use the principle of quantum state superposition to initialize the state of the quantum neuron, and determine the initial connection weight values ​​of the quantum neural network by calculating the probability amplitude values ​​of different quantum gate operations, so as to construct the initial quantum neural network structure.

[0034] S21. Quantum state superposition initialization.

[0035] The quantum neurons in the quantum neural network are represented by multiple quantum bits. According to the quantum state superposition principle, they are initialized to the superposition state of |Ψ>=α|0>+β|1>. Among them, |Ψ> represents the state vector of the quantum bit, indicating that the quantum bit is in the superposition state of |0> and |1>. α represents the probability amplitude of the quantum bit in the |0> state, β represents the probability amplitude of the quantum bit in the |1> state, and satisfies |α| 2 +|β| 2 = 1. |0> and |1> represent the two basic states of the quantum bit.

[0036] S22. Calculate the probability amplitude values ​​of different quantum gate operations.

[0037] Different quantum gate operations are applied to the initialized quantum bits, including Hadamard gate and phase gate. Each quantum gate operation will change the probability amplitude α and β of the quantum bit. The Hadamard gate is When operating on the quantum bit |Ψ>, The Hadamard gate converts a quantum bit from a |0> state or a |1> state to a superposition state of equal probability, changing the probability amplitude of the quantum bit.

[0038] The phase gate is j represents the imaginary unit. The result of the operation on the quantum bit |Ψ>=α|0>+β|1> is |Ψ>=α|0>+βe jθ |1>, by adjusting the parameter θ of the phase gate, the probability amplitude can be changed. Through a series of such quantum gate operation combinations, the probability amplitude values ​​after different quantum gate operations are calculated.

[0039] S23. Determine the initial connection weight value of the quantum neural network.

[0040] Assume the connection weight between quantum neuron A and quantum neuron B is w AB , establish a mapping relationship between the connection weights between quantum neurons and the probability amplitude after quantum gate operation. Suppose the connection weight w between quantum neuron A and quantum neuron B is AB Related to the probability amplitude α and β of the quantum bit after the quantum gate operation, define w AB =k 1 α H +k 2 β H +k 3 α P +k 4 β P , k 1 ,k 2 ,k 3 ,k 4 is the proportionality coefficient. H and β H represents the probability amplitude after the Hadamard gate operation, α P and β P Indicates the probability amplitude after the phase gate operation. In this way, the initial connection weight value of the quantum neural network is determined according to the calculated probability amplitude value, thereby constructing the initial quantum neural network structure.

[0041] S30, generating an encryption key based on the quantum bits of the quantum neural network output layer.

[0042] The encryption key is converted from the quantum bit measurement results of the quantum neural network output layer through a hash algorithm. In the communication data encryption link, the one-time pad encryption algorithm is used to perform a bitwise XOR operation on the aircraft communication data to be transmitted and the encryption key to obtain the encrypted data ciphertext. This process converts the original data into ciphertext form, making it difficult to decipher the data without the corresponding key even if the data is intercepted during the transmission of the communication channel, effectively preventing the data from being stolen and tampered with, and ensuring the confidentiality of the communication content.

[0043] S31. Select random seed data and encode it into a format suitable for quantum neural network input.

[0044] The generation of encryption keys should first select a specific random seed data, which is a randomly generated digital sequence or obtained from a secure random number generator. The random seed data is encoded into a format suitable for quantum neural network input, and the digital sequence is converted into a quantum bit sequence. Let the digital sequence be S = {s 1 ,s 2 ,...,s n}, convert the digital sequence into binary representation, the binary sequence is B = {b 1 ,b 2 ,...,b n}, for each binary bit b i ∈{0, 1}, the corresponding quantum bit state is The quantum bit sequence corresponding to the entire digital sequence is n represents the number of binary numbers in the entire sequence.

[0045] S32, inputting the encoded random seed data into the quantum neural network to measure the result.

[0046] The encoded random seed data is input into the quantum neural network, and the quantum neural network operates on the input data according to its internal quantum gate operations and connection weights. During the operation, quantum phenomena such as quantum state evolution and entanglement occur between quantum bits. In the quantum neural network, quantum bits realize quantum state evolution through quantum gate operations. init >For each single qubit |ψ i >Perform Hadamard gate operations in sequence, and the single quantum bit state becomes The quantum bit sequence after the Hadamard gate operation

[0047] Right|ψ H > two adjacent qubits and Perform controlled NOT gate operation, j = 1, 3, ..., n-1. The controlled NOT gate operation matrix is ​​CNOT, and the quantum state composed of two quantum bits is After the controlled NOT gate operation, it becomes The quantum bit sequence passing through the output layer of the quantum neural network is |ψ CNOT >.

[0048] The quantum bit sequence |ψ of the output layer of the quantum neural network CNOT >Measurement is performed. Suppose that when a certain quantum bit is measured, it is in the state |ψ>=α|0>+β|1>. The probability that the measurement result is |0> is P(|0>)=|α| 2 , the probability that the measurement result is |1> is P(|1>)=|β| 2 , let |ψ CNOT Each qubit in > is measured N times, and the number of times the measurement result is |0> is n 0 , the number of times the measurement result is |1> is n 1 , calculate the statistic used to represent the measurement results Since the measurement results of quantum bits are random, each measurement will produce a different result, but by taking the average of multiple measurements, a relatively stable value can be obtained. The final measurement result value is determined by the majority voting rule.

[0049] S33. Convert the result measurement of the quantum neural network output layer into an encryption key value of fixed length through a hash algorithm.

[0050] The measurement result value D is converted into a fixed-length encryption key value through a hash algorithm for subsequent encryption operations. The measurement result value is used as the input of the hash algorithm. The processing process of the hash algorithm is to fill the measurement result value to a fixed length, which is a message L. A 64-bit block is attached to the padded message, and the block represents the original length L of the message in binary. The total length of the message after padding and length attachment is an integer multiple of 512. The initial hip-hop value is represented in hexadecimal, and the padded message is divided into several 512-bit blocks, and each block is processed in turn. The sub-blocks are expanded through a variety of logical function operations, and these functions are used to process the expanded sub-blocks. At the same time, iterative operations are performed in combination with the initial hash value and some constants. The hash value is updated at each iteration. After the compression function operation is completed for all 512-bit blocks in turn, the 8 32-bit hash values ​​obtained are finally connected to form a 256-bit hash value, which is converted into hexadecimal form as a fixed-length hash value H(D), which is the encryption key value.

[0051] S40. For the aircraft communication data to be transmitted, the encrypted data ciphertext is obtained according to the encryption key, the key is generated and distributed using the quantum key distribution technology, and the ciphertext and the key are transmitted through the communication channel.

[0052] The aircraft communication data to be transmitted is converted into binary data form through the one-time pad encryption algorithm. According to the generated encryption key value, it is also converted into a binary key sequence of the same length. The binary data to be transmitted is subjected to bitwise XOR operation with the key sequence bit by bit to obtain the encrypted data ciphertext value. Let the plaintext be P, that is, the sequence of aircraft communication data to be transmitted converted into binary form, and the key be H(D), that is, the sequence of encryption key values ​​obtained by the encryption key generation step converted into binary form, and the ciphertext calculation formula be: It is the result of bitwise XOR of plaintext and key, and is used for transmission in the communication channel. Represents a bitwise exclusive-or operation.

[0053] The encrypted data ciphertext value is sent through the aircraft's communication channel. Satellite communication links and microwave communication links are used as communication channels. Satellite communication links can provide global or large-area coverage, suitable for long-distance communications, and can maintain communications even when ground infrastructure is damaged. Microwave communication links are suitable for short to medium-distance communications. The two communication methods are combined and switched to each other when necessary to improve communication reliability. During the transmission process, it will be affected by noise interference, signal attenuation, etc., and corresponding channel coding and modulation technologies need to be adopted to ensure reliable data transmission.

[0054] The key γ is generated and distributed using quantum key distribution technology. The sender sends photons with random polarization states through a quantum channel, and the receiver randomly selects a measurement basis for measurement. Both parties compare some measurement results through a public channel and select the measurement results under the same measurement basis as the key.

[0055] The expression formula of the ciphertext W after passing through the aircraft's communication channel is: Among them, C is the ciphertext calculated by the plaintext and the key, It indicates that error correction coding corrects errors that occur in ciphertext in the communication channel. Error correction coding improves the reliability of data transmission by adding redundant information and can effectively restore the original data even in the presence of noise. η represents the adjustment factor, which reflects the strength of error correction coding. BER init Indicates the initial bit error rate. log 2 (R)(1-σ×SNR min) represents quadrature amplitude modulation, which efficiently transmits a large amount of information by changing the amplitude and phase of the carrier. R represents the modulation order of quadrature amplitude modulation, and σ represents the adjustment factor, which represents the influence of the minimum signal-to-noise ratio on the modulation efficiency. SNR min Indicates the minimum signal-to-noise ratio. represents the impact factor of the satellite communication link, Represents the impact factor of the microwave communication link. When one communication method is used, the impact factor of the other communication method is not included in the formula. represents the energy loss when the ciphertext is transmitted between the earth and the satellite, Indicates the signal attenuation caused by gases, water vapor, etc. in the atmosphere, δ s represents the weight factor, balancing the relative importance between path loss and atmospheric attenuation, N s Represents noise interference such as thermal noise and cosmic background radiation. It indicates the energy loss of a signal when it propagates on the ground or in a short distance space. Indicates the impact of physical obstacles within the line of sight on the signal, P m It means that the signal reaches the receiving end through different paths, resulting in changes in phase and amplitude. s Represents the sensitivity coefficient of the satellite communication link, υ m Represents the sensitivity coefficient of the microwave communication link, T s represents the ideal threshold of the satellite communication link, T m Represents the ideal threshold of microwave communication link. The exponential function is used to simulate the trend of link performance changing with the influencing factors.

[0056] S50: The receiving end receives the ciphertext, decrypts it, and verifies the security of the ciphertext during transmission.

[0057] The receiving end first obtains the encryption key value distributed by quantum key distribution technology. The quantum key distribution device stores the key in a specific secure storage medium, and the receiving end reads the encryption key value from the medium. The key value has undergone strict security verification during the quantum key distribution process to ensure its security. Prepare for subsequent decryption operations.

[0058] After receiving the ciphertext and using the encryption key value to pass the security verification, the encrypted data ciphertext value received is converted into binary form. Decryption is performed using the reverse process of the one-time pad encryption algorithm, that is, a bitwise XOR operation is performed on the ciphertext binary sequence and the encryption key binary sequence.

[0059] Convert the decrypted binary sequence into the original data format. If the original data is flight status data, convert the binary data into the corresponding numerical value according to the data encoding rules. If the original data is multimedia data such as audio and images, it is also necessary to restore the binary data to audio signals or image pixel data according to the corresponding multimedia data decoding standards.

[0060] The data integrity and security of the cracked ciphertext are verified, and the receiving end obtains the key security verification value and bit error rate during the quantum key distribution process. The bit error rate is compared with the pre-set threshold. If the bit error rate is within an acceptable range, it means that the key has not been tampered with during the transmission process, and the integrity and security of the data decrypted based on the key are guaranteed; if the bit error rate exceeds the threshold, it indicates that the data may be at risk and needs further investigation. The sender may be required to resend the data or conduct more in-depth security testing. At the same time, the sender calculates the hash value of the original data and sends it together. The receiver calculates the hash value of the received decrypted data and compares whether the two hash values ​​are consistent to verify that the data has not been modified during transmission.

[0061] Embodiment 2

[0062] like Figure 2 As shown, Embodiment 2 of the present application provides a high-reliability aircraft communication encryption system based on a quantum neural network, comprising:

[0063] Acquisition and processing module: used to collect and pre-process the original data of aircraft communications.

[0064] Aircraft communication data comes from a wide range of sources, including sensor data on the aircraft, which is used to collect flight status data, including speed, altitude, attitude, etc., control command data transmitted by the communication module, and multimedia data such as voice and images. These data are collected through a dedicated data acquisition interface at a specific sampling frequency to ensure data integrity and real-time performance.

[0065] The collected aircraft communication data is subjected to fast Fourier transform to obtain the signal frequency distribution. The collected time domain original signal is divided into several data segments, each data segment contains N sampling points. A fast Fourier transform operation is performed on each data segment to convert the time domain signal into a frequency domain signal. The specific formula is Among them, x(n) represents the time domain signal, which is the sampling value on the time series n, representing the signal strength of the original data of the aircraft communication at a certain moment. n represents the time series index, from 0 to N-1, which represents the serial number of the sampling point, used to identify each sampling value in the time domain signal. N represents the number of signal sampling points, that is, the total number of samples taken for the time domain signal. k represents the frequency index, from 0 to N-1, representing each frequency component in the frequency domain signal. Different k values ​​correspond to different frequencies. X(k) represents the frequency domain signal, which is the signal strength at frequency k after fast Fourier transform, reflecting the energy distribution of the original time domain signal at this frequency.

[0066] Combined with the sliding average filtering algorithm, the signal strength value after noise reduction is calculated. For the frequency domain signal after fast Fourier transform, a sliding average window is set with a window length of M. The signal in the window is averaged by moving one sampling point each time to obtain the signal strength value after noise reduction. The specific formula is: Among them, X(n) represents the input signal, y(n) represents the filtered output signal, which is the noise reduction signal strength value obtained after sliding average filtering, and M represents the length of the sliding average window, which determines the number of signal points involved in the average calculation.

[0067] According to the frequency distribution calculated by fast Fourier transform and the signal strength value after sliding average filtering, the noise signal that obviously deviates from the normal range is removed. The denoised signal is normalized and the signal value range is mapped to the [0,1] interval.

[0068] Construction module: including initialization submodule, probability amplitude value submodule, and weight submodule.

[0069] Initialization submodule: used for quantum state superposition initialization.

[0070] The quantum neurons in the quantum neural network are represented by multiple quantum bits. According to the quantum state superposition principle, they are initialized to the superposition state of |Ψ>=α|0>+β|1>. Among them, |Ψ> represents the state vector of the quantum bit, indicating that the quantum bit is in the superposition state of |0> and |1>. α represents the probability amplitude of the quantum bit in the |0> state, β represents the probability amplitude of the quantum bit in the |1> state, and satisfies |α| 2 +|β| 2 = 1. |0> and |1> represent the two basic states of the quantum bit.

[0071] Probability amplitude numerical submodule: used to calculate the probability amplitude values ​​of different quantum gate operations.

[0072] Different quantum gate operations are applied to the initialized quantum bits, including Hadamard gate and phase gate. Each quantum gate operation will change the probability amplitude α and β of the quantum bit. The Hadamard gate is When operating on the quantum bit |Ψ>, The Hadamard gate converts a quantum bit from a |0> state or a |1> state to a superposition state of equal probability, changing the probability amplitude of the quantum bit.

[0073] The phase gate is j represents the imaginary unit. The result of the operation on the quantum bit |Ψ>=α|0>+β|1> is |Ψ>=α|0>+βe jθ |1>, by adjusting the parameter θ of the phase gate, the probability amplitude can be changed. Through a series of such quantum gate operation combinations, the probability amplitude values ​​after different quantum gate operations are calculated.

[0074] Weight submodule: used to determine the initial connection weight values ​​of the quantum neural network.

[0075] Assume the connection weight between quantum neuron A and quantum neuron B is w AB , establish a mapping relationship between the connection weights between quantum neurons and the probability amplitude after quantum gate operation. Suppose the connection weight w between quantum neuron A and quantum neuron B is AB Related to the probability amplitude α and β of the quantum bit after the quantum gate operation, define w AB =k 1 α H +k 2 β H +k 3 α P +k 4 β P , k 1 ,k 2 ,k 3 ,k 4 is the proportionality coefficient. H and β H represents the probability amplitude after the Hadamard gate operation, α P and β P Indicates the probability amplitude after the phase gate operation. In this way, the initial connection weight value of the quantum neural network is determined according to the calculated probability amplitude value, thereby constructing the initial quantum neural network structure.

[0076] Key generation module: includes encoding submodule, result measurement submodule and hash conversion submodule.

[0077] Encoding submodule: selects random seed data and encodes it into a format suitable for quantum neural network input.

[0078] The encryption key is converted from the quantum bit measurement results of the quantum neural network output layer through a hash algorithm. In the communication data encryption link, the one-time pad encryption algorithm is used to perform a bitwise XOR operation on the aircraft communication data to be transmitted and the encryption key to obtain the encrypted data ciphertext. This process converts the original data into ciphertext form, making it difficult to decipher the data without the corresponding key even if the data is intercepted during the transmission of the communication channel, effectively preventing the data from being stolen and tampered with, and ensuring the confidentiality of the communication content.

[0079] The generation of encryption keys should first select a specific random seed data, which is a randomly generated digital sequence or obtained from a secure random number generator. The random seed data is encoded into a format suitable for quantum neural network input, and the digital sequence is converted into a quantum bit sequence. Let the digital sequence be S = {s 1 ,s 2 ,...,s n}, convert the digital sequence into binary representation, the binary sequence is B = {b 1 ,b 2 ,...,b n}, for each binary bit b i ∈{0, 1}, the corresponding quantum bit state is The quantum bit sequence corresponding to the entire digital sequence is n represents the number of binary numbers in the entire sequence.

[0080] Result measurement submodule: Input the encoded random seed data into the quantum neural network for result measurement.

[0081] The encoded random seed data is input into the quantum neural network, and the quantum neural network operates on the input data according to its internal quantum gate operations and connection weights. During the operation, quantum phenomena such as quantum state evolution and entanglement occur between quantum bits. In the quantum neural network, quantum bits realize quantum state evolution through quantum gate operations. init >For each single qubit |ψ i >Perform Hadamard gate operations in sequence, and after the operation, the single quantum bit state becomes |ψ i H >=H|ψ i >, the quantum bit sequence after the Hadamard gate operation

[0082] Right|ψ H > two adjacent qubits and Perform controlled NOT gate operation, j = 1, 3, ..., n-1. The controlled NOT gate operation matrix is ​​CNOT, and the quantum state composed of two quantum bits is After the controlled NOT gate operation, it becomes The quantum bit sequence passing through the output layer of the quantum neural network is |ψ CNOT >.

[0083] The quantum bit sequence |ψ of the output layer of the quantum neural network CNOT >Measurement is performed. Suppose that when a certain quantum bit is measured, it is in the state |ψ>=α|0>+β|1>. The probability that the measurement result is |0> is P(|0>)=|α| 2 , the probability that the measurement result is |1> is P(|1>)=|β| 2 , let |ψ CNOT Each qubit in > is measured N times, and the number of times the measurement result is |0> is n 0 , the number of times the measurement result is |1> is n 1 , calculate the statistic used to represent the measurement results Since the measurement results of quantum bits are random, each measurement will produce a different result, but by taking the average of multiple measurements, a relatively stable value can be obtained. The final measurement result value is determined by the majority voting rule.

[0084] Hash conversion submodule: converts the result measurement of the quantum neural network output layer into a fixed-length encryption key value through a hash algorithm.

[0085] The measurement result value D is converted into a fixed-length encryption key value through a hash algorithm for subsequent encryption operations. The measurement result value is used as the input of the hash algorithm. The processing process of the hash algorithm is to fill the measurement result value to a fixed length, which is a message L. A 64-bit block is attached to the padded message, and the block represents the original length L of the message in binary. The total length of the message after padding and length attachment is an integer multiple of 512. The initial hip-hop value is represented in hexadecimal, and the padded message is divided into several 512-bit blocks, and each block is processed in turn. The sub-blocks are expanded through a variety of logical function operations, and these functions are used to process the expanded sub-blocks. At the same time, iterative operations are performed in combination with the initial hash value and some constants. The hash value is updated at each iteration. After the compression function operation is completed for all 512-bit blocks in turn, the 8 32-bit hash values ​​obtained are finally connected to form a 256-bit hash value, which is converted into hexadecimal form as a fixed-length hash value H(D), which is the encryption key value.

[0086] Communication channel module: For the aircraft communication data to be transmitted, the encrypted data ciphertext is obtained based on the encryption key, and the key is generated and distributed using quantum key distribution technology, and the ciphertext and key are transmitted through the communication channel.

[0087] The aircraft communication data to be transmitted is converted into binary data form through the one-time pad encryption algorithm. According to the generated encryption key value, it is also converted into a binary key sequence of the same length. The binary data to be transmitted is subjected to bitwise XOR operation with the key sequence bit by bit to obtain the encrypted data ciphertext value. Let the plaintext be P, that is, the sequence of aircraft communication data to be transmitted converted into binary form, and the key be H(D), that is, the sequence of encryption key values ​​obtained by the encryption key generation step converted into binary form, and the ciphertext calculation formula be: It is the result of bitwise XOR of plaintext and key, and is used for transmission in the communication channel. Represents a bitwise exclusive-or operation.

[0088] The encrypted data ciphertext value is sent through the aircraft's communication channel. Satellite communication links and microwave communication links are used as communication channels. Satellite communication links can provide global or large-area coverage, suitable for long-distance communications, and can maintain communications even when ground infrastructure is damaged. Microwave communication links are suitable for short to medium-distance communications. The two communication methods are combined and switched to each other when necessary to improve communication reliability. During the transmission process, it will be affected by noise interference, signal attenuation, etc., and corresponding channel coding and modulation technologies need to be adopted to ensure reliable data transmission.

[0089] The key γ is generated and distributed using quantum key distribution technology. The sender sends photons with random polarization states through a quantum channel, and the receiver randomly selects a measurement basis for measurement. Both parties compare some measurement results through a public channel and select the measurement results under the same measurement basis as the key.

[0090] The expression formula of the ciphertext W after passing through the aircraft's communication channel is: Among them, C is the ciphertext calculated by the plaintext and the key, It indicates that error correction coding corrects errors that occur in ciphertext in the communication channel. Error correction coding improves the reliability of data transmission by adding redundant information and can effectively restore the original data even in the presence of noise. η represents the adjustment factor, which reflects the strength of error correction coding. BER init Indicates the initial bit error rate. log 2 (R)(1-σ×SNR min ) represents quadrature amplitude modulation, which efficiently transmits a large amount of information by changing the amplitude and phase of the carrier. R represents the modulation order of quadrature amplitude modulation, and σ represents the adjustment factor, which represents the influence of the minimum signal-to-noise ratio on the modulation efficiency. SNR min Indicates the minimum signal-to-noise ratio. represents the impact factor of the satellite communication link, Represents the impact factor of the microwave communication link. When one communication method is used, the impact factor of the other communication method is not included in the formula. represents the energy loss when the ciphertext is transmitted between the earth and the satellite, Indicates the signal attenuation caused by gases, water vapor, etc. in the atmosphere, δ s represents the weight factor, balancing the relative importance between path loss and atmospheric attenuation, N s Represents noise interference such as thermal noise and cosmic background radiation. It indicates the energy loss of a signal when it propagates on the ground or in a short distance space. Indicates the impact of physical obstacles within the line of sight on the signal, P m It means that the signal reaches the receiving end through different paths, resulting in changes in phase and amplitude. s Represents the sensitivity coefficient of the satellite communication link, υ m Represents the sensitivity coefficient of the microwave communication link, T s represents the ideal threshold of the satellite communication link, T m Represents the ideal threshold of microwave communication link. The exponential function is used to simulate the trend of link performance changing with the influencing factors.

[0091] Receiving and verification module: The receiving end receives the ciphertext and decrypts and verifies the security of the ciphertext during transmission.

[0092] The receiving end first obtains the encryption key value distributed by quantum key distribution technology. The quantum key distribution device stores the key in a specific secure storage medium, and the receiving end reads the encryption key value from the medium. The key value has undergone strict security verification during the quantum key distribution process to ensure its security. Prepare for subsequent decryption operations.

[0093] After receiving the ciphertext and using the encryption key value to pass the security verification, the encrypted data ciphertext value received is converted into binary form. Decryption is performed using the reverse process of the one-time pad encryption algorithm, that is, a bitwise XOR operation is performed on the ciphertext binary sequence and the encryption key binary sequence.

[0094] Convert the decrypted binary sequence into the original data format. If the original data is flight status data, convert the binary data into the corresponding numerical value according to the data encoding rules. If the original data is multimedia data such as audio and images, it is also necessary to restore the binary data to audio signals or image pixel data according to the corresponding multimedia data decoding standards.

[0095] The data integrity and security of the cracked ciphertext are verified, and the receiving end obtains the key security verification value and bit error rate during the quantum key distribution process. The bit error rate is compared with the pre-set threshold. If the bit error rate is within an acceptable range, it means that the key has not been tampered with during the transmission process, and the integrity and security of the data decrypted based on the key are guaranteed; if the bit error rate exceeds the threshold, it indicates that the data may be at risk and needs further investigation. The sender may be required to resend the data or conduct more in-depth security testing. At the same time, the sender calculates the hash value of the original data and sends it together. The receiver calculates the hash value of the received decrypted data and compares whether the two hash values ​​are consistent to verify that the data has not been modified during transmission.

[0096] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made on the basis of the technical solution of the present invention should be included in the scope of protection of the present invention.

Claims

1. A high-reliability aircraft communication encryption method based on quantum neural network, characterized in that: include: S10, collecting and preprocessing aircraft communication raw data; S20, using the quantum state superposition principle to initialize the quantum neuron state, and determining the initial connection weight value of the quantum neural network by calculating the probability amplitude value of different quantum gate operations, thereby constructing the initial quantum neural network structure; S30, generating an encryption key according to the quantum bits of the output layer of the quantum neural network; S40, for the aircraft communication data to be transmitted, obtaining encrypted data ciphertext according to the encryption key, generating and distributing the key using quantum key distribution technology, and transmitting the ciphertext and the key through the communication channel; S50: The receiving end receives the ciphertext, decrypts it, and verifies the security of the ciphertext during transmission.

2. A high-reliability aircraft communication encryption method based on quantum neural network as claimed in claim 1, characterized in that: The preprocessing of the aircraft communication raw data includes using fast Fourier transform to obtain the signal frequency distribution and using the sliding average filter algorithm to calculate the signal strength value after noise reduction.

3. A high-reliability aircraft communication encryption method based on quantum neural network as claimed in claim 1, characterized in that: Constructing the initial quantum neural network structure is divided into the following sub-steps: quantum state superposition initialization; calculating the probability amplitude values ​​of different quantum gate operations; determining the initial connection weight values ​​of the quantum neural network; and constructing the initial quantum neural network structure based on the initial connection weight values.

4. A high-reliability aircraft communication encryption method based on quantum neural network as claimed in claim 1, characterized in that: Generating encryption keys is divided into the following sub-steps: selecting random seed data and encoding it into a format suitable for quantum neural network input; inputting the encoded random seed data into the quantum neural network for result measurement; and converting the result measurement of the output layer of the quantum neural network into a fixed-length encryption key value through a hash algorithm.

5. A high-reliability aircraft communication encryption method based on quantum neural network as claimed in claim 1, characterized in that: The encrypted data ciphertext is the result of bitwise XOR of the aircraft communication data and the encryption key.

6. A high-reliability aircraft communication encryption method based on quantum neural network as claimed in claim 1, characterized in that: The ciphertext is transmitted to the sender through a communication channel, which includes a satellite communication link and a microwave communication link.

7. A high-reliability aircraft communication encryption method based on quantum neural network as claimed in claim 1, characterized in that: During the transmission process of the communication channel, it is necessary to consider the impact of different communication channels on transmission and use error correction coding and orthogonal amplitude modulation to improve the reliability of data transmission.

8. A high-reliability aircraft communication encryption system based on quantum neural network, characterized in that: include: Acquisition and processing module: used to collect and pre-process the original data of aircraft communication; Building module: Use the principle of quantum state superposition to initialize the quantum neuron state, calculate the probability amplitude values ​​of different quantum gate operations, determine the initial connection weight values ​​of the quantum neural network, and thus construct the initial quantum neural network structure; Key generation module: Generates encryption keys based on quantum bits in the output layer of the quantum neural network; Communication channel module: for aircraft communication data to be transmitted, the encrypted data ciphertext is obtained according to the encryption key, the key is generated and distributed using quantum key distribution technology, and the ciphertext and key are transmitted through the communication channel; Receiving and verification module: The receiving end receives the ciphertext and decrypts and verifies the security of the ciphertext during transmission.

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